Practitioner Feedback on Lung Cancer Practice Guidelines in Ontario

Purpose:Practitioner feedback (PF) surveys are sent to practitioners who care for lung cancer patients as each new practice guideline is completed. In this study, the PF was reviewed to assess the frequency of response to the surveys, the respondents’ characteristics, the nature of the feedback, and the intention to adopt the guideline in practice.Methods:Fourteen practice guidelines (PGs) were sent to Ontario practitioners treating lung cancer, and feedback on the PGs was obtained through either an eight- or 21-item survey.Results:Between 1995 and 2002, 1198 surveys were sent to 223 practitioners. The overall response rate was 58.9% but varied by specialty (radiation and medical oncologists, 67%; thoracic surgeons, 46%; respirologists, 38%), by location of practice (cancer center, 65%; community-based practice, 55%), by geographic region of the province (highest, 72%; lowest, 42%), and by PG topic (chemotherapy, 60%; radiotherapy, 63%; combined modality therapy, 52%). The response rate to the PF surveys did not decline over time. Eighty-six percent of respondents agreed with the lung cancer guidelines and indicated that they were likely or very likely to use the PGs in their practice.Conclusion:The results suggest that practitioners view the guideline development process as credible and useful to guide practice. Whether the stated intention to use the guidelines will actually translate into practice requires further study

A phase II multicentre, open-label, proof-of-concept study of tasquinimod in hepatocellular, ovarian, renal cell, and gastric cancers

Background: Tasquinimod is a small molecule with immunomodulatory, anti-angiogenic, and anti-metastatic properties that targets the tumor microenvironment. This study aimed to obtain a clinical proof of concept that tasquinimod was active and tolerable in patients with advanced solid tumors. Patients and Methods: This early stopping design, open-label, proof-of-concept clinical trial evaluated the clinical activity of tasquinimod in four independent cohorts of patients with advanced hepatocellular (n = 53), ovarian (n = 55), renal cell (n = 38), and gastric (n = 21) cancers. Tasquinimod was given orally every day (0.5 mg/day for at least 2 weeks, with dose increase to 1 mg/day) until radiological progression according to Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 criteria, intolerable toxicity, or patient withdrawal. The primary efficacy endpoint was progression-free survival (PFS) rate according to RECIST 1.1 by central assessment. Results: Interim futility analyses at 8 weeks (6 weeks for the gastric cancer cohort) found adequate clinical activity of tasquinimod only in the hepatocellular cohort and recruitment to the other three cohorts was stopped. PFS rates were 26.9% at 16 weeks, 7.3% at 24 weeks, 13.2% at 16 weeks, and 9.5% at 12 weeks, respectively, in hepatocellular, ovarian, renal cell, and gastric cancer cohorts. The pre-defined PFS threshold was not reached in the hepatocellular cancer cohort at the second stage of the trial. The most common treatment-related adverse events were fatigue (48.5%), nausea (34.1%), decreased appetite (31.7%), and vomiting (24.6%). Conclusions: This study failed to demonstrate clinical activity of tasquinimod in heavily pre-treated patients with advanced hepatocellular, ovarian, renal cell, and gastric cancer. Trial registration: NCT01743469

Uptake of new treatment strategies for deep vein thrombosis: an international audit

Objective. Study of the uptake of new medical technologies provides useful information on the transfer of published evidence into usual practice. We conducted an audit of selected hospitals in three countries (Canada, France, and Switzerland) to identify clinical predictors of low-molecular-weight (LMW) heparin use and outpatient treatment, and to compare the pace of uptake of these new therapeutic approaches across hospitals. Design. Historical review of medical records. Setting and participants. We reviewed the medical records of 3043 patients diagnosed with deep vein thrombosis (DVT) in five Canadian, two French, and two Swiss teaching hospitals from 1994 to 1998. Measures. We explored independent clinical variables associated with LMW heparin use and outpatient treatment, and determined crude and adjusted rates of LMW heparin use and outpatient treatment across hospitals. Results. For the years studied, the overall rates of LMW heparin use and outpatient treatment in the study sample were 34.1 and 15.8%, respectively, with higher rates of use in later years. Many comorbidities were negatively associated with outpatient treatment, and risk-adjusted rates of use of these new approaches varied significantly across hospitals. Conclusion. There has been a relatively rapid uptake of LMW heparins and outpatient treatment for DVT in their early years of availability, but the pace of uptake has varied considerably across hospitals and countrie

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

Crises and collective socio-economic phenomena: simple models and challenges

Financial and economic history is strewn with bubbles and crashes, booms and busts, crises and upheavals of all sorts. Understanding the origin of these events is arguably one of the most important problems in economic theory. In this paper, we review recent efforts to include heterogeneities and interactions in models of decision. We argue that the Random Field Ising model (RFIM) indeed provides a unifying framework to account for many collective socio-economic phenomena that lead to sudden ruptures and crises. We discuss different models that can capture potentially destabilising self-referential feedback loops, induced either by herding, i.e. reference to peers, or trending, i.e. reference to the past, and account for some of the phenomenology missing in the standard models. We discuss some empirically testable predictions of these models, for example robust signatures of RFIM-like herding effects, or the logarithmic decay of spatial correlations of voting patterns. One of the most striking result, inspired by statistical physics methods, is that Adam Smith's invisible hand can badly fail at solving simple coordination problems. We also insist on the issue of time-scales, that can be extremely long in some cases, and prevent socially optimal equilibria to be reached. As a theoretical challenge, the study of so-called "detailed-balance" violating decision rules is needed to decide whether conclusions based on current models (that all assume detailed-balance) are indeed robust and generic.Comment: Review paper accepted for a special issue of J Stat Phys; several minor improvements along reviewers' comment

Generation, annotation, analysis and database integration of 16,500 white spruce EST clusters

BACKGROUND: The sequencing and analysis of ESTs is for now the only practical approach for large-scale gene discovery and annotation in conifers because their very large genomes are unlikely to be sequenced in the near future. Our objective was to produce extensive collections of ESTs and cDNA clones to support manufacture of cDNA microarrays and gene discovery in white spruce (Picea glauca [Moench] Voss). RESULTS: We produced 16 cDNA libraries from different tissues and a variety of treatments, and partially sequenced 50,000 cDNA clones. High quality 3' and 5' reads were assembled into 16,578 consensus sequences, 45% of which represented full length inserts. Consensus sequences derived from 5' and 3' reads of the same cDNA clone were linked to define 14,471 transcripts. A large proportion (84%) of the spruce sequences matched a pine sequence, but only 68% of the spruce transcripts had homologs in Arabidopsis or rice. Nearly all the sequences that matched the Populus trichocarpa genome (the only sequenced tree genome) also matched rice or Arabidopsis genomes. We used several sequence similarity search approaches for assignment of putative functions, including blast searches against general and specialized databases (transcription factors, cell wall related proteins), Gene Ontology term assignation and Hidden Markov Model searches against PFAM protein families and domains. In total, 70% of the spruce transcripts displayed matches to proteins of known or unknown function in the Uniref100 database (blastx e-value < 1e-10). We identified multigenic families that appeared larger in spruce than in the Arabidopsis or rice genomes. Detailed analysis of translationally controlled tumour proteins and S-adenosylmethionine synthetase families confirmed a twofold size difference. Sequences and annotations were organized in a dedicated database, SpruceDB. Several search tools were developed to mine the data either based on their occurrence in the cDNA libraries or on functional annotations. CONCLUSION: This report illustrates specific approaches for large-scale gene discovery and annotation in an organism that is very distantly related to any of the fully sequenced genomes. The ArboreaSet sequences and cDNA clones represent a valuable resource for investigations ranging from plant comparative genomics to applied conifer genetics

Enabling low-carbon development in poor countries

The challenges associated with achieving sustainable development goals and stabilizing the world’s climate cannot be solved without significant efforts by developing and newly-emerging countries. With respect to climate change mitigation, the main challenge for developing countries lies in avoiding future emissions and lock-ins into emission-intensive technologies, rather than reducing today’s emissions. While first best policy instruments like carbon prices could prevent increasing carbonization, those policies are often rejected by developing countries out of a concern for negative repercussions on development and long-term growth. In addition, policy environments in developing countries impose particular challenges for regulatory policy aiming to incentivize climate change mitigation and sustainable development. This chapter first discusses how climate policy could potentially interact with sustainable development and economic growth. It focuses, in particular, on the role of industrial sector development. The chapter then continues by discussing how effective policy could be designed, specifically taking developing country circumstances into account